python-typing-checker

Analyze Python type annotation coverage and quality — check mypy compliance, find untyped functions, review Protocol usage, Generic types, TypeVar constraints, and modern typing patterns. Use when auditing Python type safety, preparing for strict mypy, or enforcing type annotation standards.

Safety Notice

This listing is from the official public ClawHub registry. Review SKILL.md and referenced scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "python-typing-checker" with this command: npx skills add charlie-morrison/python-typing-checker

Python Typing Checker

Deep analysis of type annotation coverage and quality across Python codebases. Finds untyped functions, incorrect annotations, missing generics, improper Protocol usage, and patterns that break type checker inference.

Use when: auditing type safety, preparing to enable strict mypy, reviewing annotation quality, or migrating from untyped to typed Python.

Analysis Steps

1. Project Discovery

cat pyproject.toml 2>/dev/null | head -30
python3 --version 2>/dev/null

# Mypy config
cat pyproject.toml 2>/dev/null | grep -A30 '\[tool.mypy\]'
cat mypy.ini 2>/dev/null || cat setup.cfg 2>/dev/null | grep -A20 '\[mypy\]'

# py.typed marker (PEP 561)
find . -name "py.typed" -not -path '*/venv/*' 2>/dev/null
find . -name "*.pyi" -not -path '*/venv/*' 2>/dev/null | head -10
find . -name "*.py" -not -path '*/venv/*' -not -path '*/__pycache__/*' | wc -l

Determine: Python version, type checker config and strictness, whether package ships types (py.typed), project size.

2. Type Annotation Coverage

# Functions without return type annotation
grep -rn 'def [a-zA-Z_]\+(' --include="*.py" . 2>/dev/null \
  | grep -v 'venv/\|__pycache__\|_test\.py\|test_' | grep -v '\-> ' | head -30

# Completely untyped files
for f in $(find . -name "*.py" -not -path '*/venv/*' -not -path '*/__pycache__/*' \
  -not -name '*_test.py' 2>/dev/null); do
  if ! grep -q ':\s*[A-Z]\|-> \|: str\|: int\|: float\|: bool\|: list\|: dict' "$f" 2>/dev/null; then
    echo "UNTYPED: $f"
  fi
done | head -15

# Coverage estimate
total=$(grep -rc 'def ' --include="*.py" . 2>/dev/null | grep -v 'venv/' | awk -F: '{s+=$2} END {print s}')
typed=$(grep -rc '\-> ' --include="*.py" . 2>/dev/null | grep -v 'venv/' | awk -F: '{s+=$2} END {print s}')
echo "Coverage: $typed / $total functions have return type annotations"

3. Type Import Patterns

# Deprecated typing imports (use builtins in 3.9+)
grep -rn 'from typing import List\|from typing import Dict\|from typing import Tuple\|from typing import Set' \
  --include="*.py" . 2>/dev/null | grep -v 'venv/' | head -15

# from __future__ import annotations (PEP 563)
grep -rn 'from __future__ import annotations' --include="*.py" . 2>/dev/null | grep -v 'venv/' | head -10

# TYPE_CHECKING guard
grep -rn 'TYPE_CHECKING' --include="*.py" . 2>/dev/null | grep -v 'venv/' | head -10

Flag:

  • Deprecated typing imports: typing.List/Dict/Tuple/Set deprecated since 3.9 — use list/dict/tuple/set
  • Missing TYPE_CHECKING guard: types imported only for annotations should be under if TYPE_CHECKING: to avoid runtime overhead and circular imports
  • Inconsistent style: mixing List[int] and list[int] in same codebase

4. Any, Union, and Escape Hatches

# Any usage (excluding imports)
grep -rn '\bAny\b' --include="*.py" . 2>/dev/null | grep -v 'venv/\|_test\.py\|from typing' | head -20

# type: ignore comments
grep -rn 'type:\s*ignore' --include="*.py" . 2>/dev/null | grep -v 'venv/' | head -15

# cast() usage
grep -rn 'cast(' --include="*.py" . 2>/dev/null | grep -v 'venv/' | head -10

# Optional without None check patterns
grep -rn 'Optional\[' --include="*.py" . 2>/dev/null | grep -v 'venv/' | head -10

Flag:

  • Excessive Any: each Any is a hole in type safety — each usage should be justified
  • Functions returning Any: callers lose all type information
  • type: ignore without error code: should specify like # type: ignore[assignment] for maintainability
  • cast() overuse: runtime no-op that lies to the type checker — prefer isinstance narrowing
  • Optional without None handling: annotating Optional[X] but never checking for None

5. Generics, TypeVar, and Protocol

# TypeVar definitions
grep -rn 'TypeVar(' --include="*.py" . 2>/dev/null | grep -v 'venv/' | head -10

# ParamSpec (decorator typing, 3.10+)
grep -rn 'ParamSpec' --include="*.py" . 2>/dev/null | grep -v 'venv/' | head -5

# Protocol definitions
grep -rn 'class.*Protocol' --include="*.py" . 2>/dev/null | grep -v 'venv/\|from typing' | head -10

# ABC vs Protocol
grep -rn '@abstractmethod\|class.*ABC' --include="*.py" . 2>/dev/null | grep -v 'venv/' | head -10

# Complex Callable types
grep -rn 'Callable\[' --include="*.py" . 2>/dev/null | grep -v 'venv/' | head -10

# dict[str, Any] (could be TypedDict)
grep -rn 'dict\[str,\s*Any\]\|Dict\[str,\s*Any\]' --include="*.py" . 2>/dev/null | grep -v 'venv/' | head -10

Flag:

  • Unconstrained TypeVar: T = TypeVar('T') accepts anything — add bound= if function needs specific capabilities
  • Missing ParamSpec for decorators: decorators without ParamSpec lose the decorated function's signature
  • ABC where Protocol fits: if base class has no shared implementation, Protocol gives structural subtyping without inheritance
  • Complex Callable types: Callable[[str, int, Optional[dict]], Awaitable[list[str]]] — use Protocol with __call__ instead
  • dict[str, Any] for structured data: use TypedDict for type-safe key access

6. Dataclass & Async Patterns

# Dataclass issues
grep -A20 '@dataclass' --include="*.py" . 2>/dev/null | grep '^\s\+[a-z_]\+ =' | grep -v ':' | head -10

# TypedDict
grep -rn 'TypedDict' --include="*.py" . 2>/dev/null | grep -v 'venv/\|from typing' | head -10

# Async functions without return type
grep -rn 'async def' --include="*.py" . 2>/dev/null | grep -v 'venv/\|_test\.py' | grep -v '\->' | head -10

Flag:

  • Dataclass fields without types: required in strict mode
  • Mutable default in dataclass: field: list = [] shared across instances — use field(default_factory=list)
  • Async functions without return annotation: type checker infers Coroutine[Any, Any, Any]

7. Mypy Strictness Audit

grep -i 'strict\|disallow_untyped_defs\|disallow_any_generics\|warn_return_any\|check_untyped_defs' \
  pyproject.toml mypy.ini setup.cfg 2>/dev/null | head -15

Recommended strictness progression:

  1. check_untyped_defs = true — type-check bodies even without annotations
  2. no_implicit_optional = true — require explicit Optional[X] for = None
  3. warn_return_any = true — flag functions returning Any via untyped calls
  4. disallow_untyped_defs = true — require annotations on all functions
  5. disallow_any_generics = true — require type params (list[int] not list)
  6. strict = true — all strict flags (goal state)

Output Template

# Python Typing Analysis — [Project Name]

## Summary
- Files: N | Python: 3.XX | Type checker: mypy/pyright/none
- Functions with return types: N/M (XX%) | Any usages: N | type:ignore: N

## Coverage by Package
| Package | Functions | Typed | Coverage |
|---------|-----------|-------|----------|
| src/core/ | 30 | 12 | 40% |
| src/api/ | 45 | 40 | 89% |

## Critical Findings
### [C1] Function Returns Any, Callers Assume str
- **File**: src/utils/parser.py:34 — Fix: `def parse(data: bytes) -> ParseResult:`
### [C2] Optional Without None Check
- **File**: src/api/handlers.py:56 — Fix: add None guard before access

## Recommendations
1. Enable `check_untyped_defs = true` in mypy config
2. Add return types to N functions in highest-priority packages
3. Replace N deprecated `typing.List/Dict` imports with builtins
4. Add error codes to N `type: ignore` comments
5. Replace N `dict[str, Any]` with TypedDict, add `ParamSpec` to N decorators
6. Add `py.typed` marker if package is distributed as library

Tips

  • Run mypy --strict --show-error-codes . to see all strict violations
  • Use reveal_type(expr) to debug inference, typing.assert_type() (3.11+) for tests
  • Run pyright --verifytypes <package> to check exported API completeness
  • Use stubgen for .pyi stubs, monkeytype for runtime-traced annotations
  • For complex dict structures, use datamodel-code-generator to generate TypedDict from JSON

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

Security

python-code-analyz

专业Python代码分析与优化,支持语法检查、安全扫描、性能评估、复杂度分析及重构后的优化代码生成。

Registry SourceRecently Updated
1230Profile unavailable
Coding

InStreet gomoku AI

InStreet五子棋AI。在InStreet桌游室进行五子棋对局时,自动计算最佳落子并提交。支持威胁检测,优先防守对手的活三/冲四。

Registry SourceRecently Updated
2630Profile unavailable
Coding

Productivity Bot

Automation bot for productivity tasks including data processing, scheduled notifications, and workflow optimization.

Registry SourceRecently Updated
2.3K0Profile unavailable
Coding

Beta Backtester

Professional backtesting framework for trading strategies. Tests SMA crossover, RSI, MACD, Bollinger Bands, and custom strategies on historical data. Generat...

Registry SourceRecently Updated
1180Profile unavailable